Identifying Sensitive Measures of Cognitive Decline at Different Clinical Stages of Alzheimer's Disease

Digital cognitive assessments as low-burden markers for predicting future cognitive decline and tau accumulation across the Alzheimer's spectrum

BACKGROUND

Digital cognitive assessments, particularly those that can be done at home, present as low-burden biomarkers for participants and patients alike, but their effectiveness in the diagnosis of Alzheimer's disease (AD) or predicting its trajectory is still unclear. Here, we assessed what utility or added value these digital cognitive assessments provide for identifying those at high risk of cognitive decline.

METHODS

We analyzed >500 Alzheimer's Disease Neuroimaging Initiative participants who underwent a brief digital cognitive assessment and amyloid beta (Aβ)/tau positron emission tomography scans, examining their ability to distinguish cognitive status and predict cognitive decline.

RESULTS

Performance on the digital cognitive assessment was superior to both cortical Aβ and entorhinal tau in detecting mild cognitive impairment and future cognitive decline, with mnemonic discrimination deficits emerging as the most critical measure for predicting decline and future tau accumulation.

DISCUSSION

Digital assessments are effective at identifying at-risk individuals, supporting their utility as low-burden tools for early AD detection and monitoring.

HIGHLIGHTS

Performance on digital cognitive assessments predicts progression to mild cognitive impairment at a higher proficiency compared to amyloid beta and tau. Deficits in mnemonic discrimination are indicative of future cognitive decline. Impaired mnemonic discrimination predicts future entorhinal and inferior temporal tau.

Automated deep learning segmentation of neuritic plaques and neurofibrillary tangles in Alzheimer disease brain sections using a proprietary software

Neuropathological diagnosis of Alzheimer disease (AD) relies on semiquantitative analysis of phosphorylated tau-positive neurofibrillary tangles (NFTs) and neuritic plaques (NPs), without consideration of lesion heterogeneity in individual cases. We developed a deep learning workflow for automated annotation and segmentation of NPs and NFTs from AT8-immunostained whole slide images (WSIs) of AD brain sections. Fifteen WSIs of frontal cortex from 4 biobanks with varying tissue quality, staining intensity, and scanning formats were analyzed. We established an artificial intelligence (AI)-driven iterative procedure to improve the generation of expert-validated annotation datasets for NPs and NFTs thereby increasing annotation quality by >50%. This strategy yielded an expert-validated annotation database with 5013 NPs and 5143 NFTs. We next trained two U-Net convolutional neural networks for detection and segmentation of NPs or NFTs, achieving high accuracy and consistency (mean Dice similarity coefficient: NPs, 0.77; NFTs, 0.81). The workflow showed high generalization performance across different cases. This study serves as a proof-of-concept for the utilization of proprietary image analysis software (Visiopharm) in the automated deep learning segmentation of NPs and NFTs, demonstrating that AI can significantly improve the annotation quality of complex neuropathological features and enable the creation of highly precise models for identifying these markers in AD brain sections.

Synaptic protein CSF levels relate to memory scores in individuals without dementia

INTRODUCTION

We investigated how cerebrospinal fluid levels of synaptic proteins associate with memory function in normal cognition (CN) and mild cognitive impairment (MCI), and investigated the effect of amyloid positivity on these associations.

METHODS

We included 242 CN (105(43%) abnormal amyloid), and 278 MCI individuals (183(66%) abnormal amyloid) from EMIF-AD MBD and ADNI. For 181 (EMIF-AD MBD) and 36 (ADNI) proteins with a synaptic annotation in SynGO, associations with word learning recall were analysed with linear models.

RESULTS

Subsets of synaptic proteins showed lower levels with worse recall in preclinical AD (EMIF-AD MBD: 7, ADNI: 5 proteins, none overlapping), prodromal AD (EMIF-AD MBD only, 27 proteins) and non-AD MCI (EMIF-AD MBD: 1, ADNI: 7 proteins). The majority of these associations were specific to these groups.

DISCUSSION

Synaptic disturbance-related memory impairment occurred very early in AD, indicating it may be relevant to develop therapies targeting the synapse early in the disease.

Prediction of Mild Cognitive Impairment Status: Pilot Study of Machine Learning Models Based on Longitudinal Data From Fitness Trackers

BACKGROUND

Early signs of Alzheimer disease (AD) are difficult to detect, causing diagnoses to be significantly delayed to time points when brain damage has already occurred and current experimental treatments have little effect on slowing disease progression. Tracking cognitive decline at early stages is critical for patients to make lifestyle changes and consider new and experimental therapies. Frequently studied biomarkers are invasive and costly and are limited for predicting conversion from normal to mild cognitive impairment (MCI).

OBJECTIVE

This study aimed to use data collected from fitness trackers to predict MCI status.

METHODS

In this pilot study, fitness trackers were worn by 20 participants: 12 patients with MCI and 8 age-matched controls. We collected physical activity, heart rate, and sleep data from each participant for up to 1 month and further developed a machine learning model to predict MCI status.

RESULTS

Our machine learning model was able to perfectly separate between MCI and controls (area under the curve=1.0). The top predictive features from the model included peak, cardio, and fat burn heart rate zones; resting heart rate; average deep sleep time; and total light activity time.

CONCLUSIONS

Our results suggest that a longitudinal digital biomarker differentiates between controls and patients with MCI in a very cost-effective and noninvasive way and hence may be very useful for identifying patients with very early AD who can benefit from clinical trials and new, disease-modifying therapies.

Driving among individuals with chronic conditions: A systematic review of applied research using kinematic driving sensors

BACKGROUND

Kinematic driving data studies are a novel methodology relevant to health care, but prior studies have considerable variance in their methods, populations, and findings suggesting a need for critical analysis and appraisal for feasibility and methodological guidelines.

METHODS

We assessed kinematic driving studies of adults with chronic conditions for study feasibility, characteristics, and key findings, to generate recommendations for future study designs, and to identify promising directions for applications of kinematic driving data. PRISMA was used to guide the review and searches included PubMed, CINAHL, and Compendex. Of 379 abstract/titles screened, 49 full-text articles were reviewed, and 29 articles met inclusion criteria of analyzing trip-level kinematic driving data from adult drivers with chronic conditions.

RESULTS

The predominant chronic conditions studied were Alzheimer's disease and related Dementias, obstructive sleep apnea, and diabetes mellitus. Study objectives included feasibility testing of kinematic driving data collection in the context of chronic conditions, comparisons of simulation with real-world kinematic driving behavior, assessments of driving behavior effects associated with chronic conditions, and prognostication or disease classification drawn from kinematic driving data. Across the studies, there was no consensus on devices, measures, or sampling parameters; however, studies showed evidence that driving behavior could reliably differentiate between adults with chronic conditions and healthy controls.

CONCLUSIONS

Vehicle sensors can provide driver-specific measures relevant to clinical assessment and interventions. Using kinematic driving data to assess and address driving measures of individuals with multiple chronic conditions is positioned to amplify a functional outcome measure that matters to patients.

Cognitive and Functional Change Over Time in Cognitively Healthy Individuals According to Alzheimer Disease Biomarker-Defined Subgroups

BACKGROUND AND OBJECTIVES

It is unclear to what extent cognitive outcome measures are sensitive to capture decline in Alzheimer disease (AD) prevention trials. We aimed to analyze the sensitivity to changes over time of a range of neuropsychological tests in several cognitively unimpaired, biomarker-defined patient groups.

METHODS

Cognitively unimpaired individuals from the Amsterdam Dementia Cohort and the SCIENCe project with available AD biomarkers, obtained from CSF, PET scans, and plasma at baseline, were followed over time (4.5 ± 3.1 years, range 0.6-18.9 years). Based on common inclusion criteria for clinical trials, we defined groups (amyloid, phosphorylated tau [p-tau], APOE ε4). Linear mixed models, adjusted for age, sex, and education, were used to estimate change over time in neuropsychological tests, a functional outcome, and 2 cognitive composite measures. Standardized regression coefficients of time in years (βtime) were reported as outcome of interest. We analyzed change over time with full follow-up, as well as with follow-up limited to 1.5 and 3 years.

RESULTS

We included 387 individuals (aged 61.7 ± 8.6 years; 44% female) in the following (partly overlapping) biomarker groups: APOE ε4 carriers (n = 212), amyloid-positive individuals (n = 109), amyloid-positive APOE ε4 carriers (n = 66), CSF p-tau-positive individuals (n = 127), plasma p-tau-positive individuals (n = 71), and amyloid and CSF p-tau-positive individuals (n = 50), or in a control group (normal biomarkers; n = 65). An executive functioning task showed most decline in all biomarker groups (βtime range -0.30 to -0.71), followed by delayed word list recognition (βtime range -0.18 to -0.50). Functional decline (βtime range -0.17 to -0.63) was observed in all, except the CSF and plasma tau-positive groups. Both composites showed comparable amounts of change (βtime range -0.12 to -0.62) in all groups, except plasma p-tau-positive individuals. When limiting original follow-up duration, many effects disappeared or even flipped direction.

DISCUSSION

In conclusion, functional, composite, and neuropsychological outcome measures across all cognitive domains detect changes over time in various biomarker-defined groups, with changes being most evident among individuals with more AD pathology. AD prevention trials should use sufficiently long follow-up duration and/or more sensitive outcome measures to optimally capture subtle cognitive changes over time.

Sleep Quality and Cognitive Abilities in the Greek Cohort of Epirus Health Study

Purpose

Sleep is essential to all human body functions as well as brain functions. Inadequate sleep quantity and poor sleep quality have been shown to directly affect cognitive functioning and especially memory. The primary aim of the present study was to investigate the association of sleep quality with cognitive abilities cross-sectionally in a middle-aged Greek population and secondarily to examine this association prospectively in a smaller group of these participants.

Patients and Methods

A total of 2112 healthy adults aged 25-70 years (mean: 46.7±11.5) from the Epirus Health Study cohort were included in the analysis and 312 of them participated in secondary prospective analysis. Sleep quality was measured by the Pittsburgh Sleep Quality Index (PSQI) scale and cognition was assessed in primary cross-sectional analyses with three neuropsychological tests, namely the Verbal Fluency test, the Logical Memory test and the Trail Making test, and in secondary prospective analyses with online versions of Posner cueing task, an emotional recognition task, the Corsi block-tapping task and the Stroop task. Statistical analysis was performed using multivariable linear regression models adjusted for age, sex, education, body mass index and alcohol consumption.

Results

Attention/processing speed was the only cognitive domain associated cross-sectionally with PSQI score. Specifically, participants with better self-reported sleep quality performed faster on the Trail Making Test - Part A (β= 0.272 seconds, 95% CI 0.052, 0.493).

Conclusion

Further studies are needed to clarify the association of sleep quality with cognition, especially in middle-aged people that are still in productive working years.

Chronic memantine disrupts spatial memory and up-regulates Htr1a gene expression in the hippocampus of GPR39 (zinc-sensing receptor) KO male mice

GPR39 is a receptor involved in zincergic neurotransmission, and its role in regulating psychological functions is an active area of research. The purported roles of GPR39 at the cellular level include regulation of inflammatory and oxidative stress response, and modulation of GABAergic and endocannabinoid neurotransmission. GPR39 knock-out (KO) mice exhibit episodic-like and spatial memory (ELM and SM, respectively) deficits throughout their lifetime, and are similar in that respect to senescent wild-type (WT) conspecifics. Since a role for zinc has been postulated in neurodegenerative disorders, in this study we investigated the possibility of a pharmacological rescue of both types of declarative memory with memantine - a noncompetitive NMDAR antagonist used for slowing down dementia; or, a putative GPR39 agonist - TC-G 1008. First, we tested adult WT and GPR39KO male mice under acute 5 mg/kg memantine or vehicle treatment in an object recognition task designed to simultaneously probe the "what?", "where?" and "when?" components of ELM. Next, we investigated the impact of chronic memantine or TC-G 1008 on ELM and SM (Morris water maze, MWM) in both WT and GPR39KO mice. Following chronic experiments, we assessed with qRT-PCR hippocampal gene expression of targets previously associated with GPR39. We report: no effects of acute memantine on ELM; a tendency to improve the "where?" component of ELM in both WT and GPR39 KO mice following 12 days of memantine; and, a disruption of SM in GPR39KO mice after 24 days of memantine treatment. The latter result was associated with upregulation of Htr1a hippocampal expression.

Utility of the Comprehensive Trail Making Test in the Assessment of Mild Cognitive Impairment in Older Patients

INTRODUCTION

The purpose of this study is to determine the usefulness of the CTMT (Comprehensive Trail Making Test) in diagnosing mild cognitive impairment in older patients. The test is used to assess executive functions, of which impairment is already observed in the early stages of the neurodegenerative process.

MATERIALS AND METHODS

The study includes 98 patients of a geriatric ward assigned to 2 groups of 49 patients each: patients diagnosed with a mild cognitive impairment and patients without a cognitive impairment, constituting the control group (group K). A set of screening tests was used in the initial study: the MMSE (Mini-Mental State Examination), MoCA (Montreal Cognitive Assessment), and CDT (Clock Drawing Test), GDS (Geriatric Depression Scale). The second study included the performance of the CTMT; the performance indicator was the time of performance.

RESULTS

Statistically significant differences are obtained between patients with mild cognitive impairments and those in cognitive normality in the performance of the CTMT test (p < 0.01). Patients with MCIs took longer to complete all trails of the test. To identify cognitive impairment, cutoff points were proposed for the CTMT total score and the other test trails. The CTMT overall score and CTMT 5 scored the highest AUCs (CTMT overall score = 0.77, CTMT Trail 5 = 0.80).

CONCLUSIONS

The Comprehensive Trail Making Test may be useful in diagnosing mild cognitive impairment as a complementary screening tool.

Evaluating memory testing to distinguish dementia severity among White, Black, and Spanish-speaking individuals in the Uniform Data Set (UDS)

INTRODUCTION

Little work has compared the effectiveness of using multiple types of memory tests alone or in combination to distinguish dementia severity in diverse research cohorts including Black individuals and Spanish speakers. Here we evaluate word list and paragraph recall tests to distinguish cognitively normal, mild cognitively impaired, and those with Alzheimer's disease in diverse cohorts.

METHODS

Using Uniform Data Set (UDS) and site-specific supplemental data, logistic regression models and receiver operating characteristic-area under the curve were used to compare paragraph recall versus word list in differentiating among Clinical Dementia Rating (CDR) scale level.

RESULTS

Results reveal high discriminability for all groups and no difference between either test in distinguishing between CDR levels. Combining tests improved discriminability for the whole group but did not for Black individuals or Spanish speakers.

DISCUSSION

Our findings indicate that using multiple memory tests may not improve differentiation between cognitive impairment levels for diverse cohorts. The burden of added testing may be a barrier for maximizing inclusion of under-represented groups in research.

Mayo-PACC: A parsimonious preclinical Alzheimer's disease cognitive composite comprised of public-domain measures to facilitate clinical translation

INTRODUCTION

We aimed to define a Mayo Preclinical Alzheimer's disease Cognitive Composite (Mayo-PACC) that prioritizes parsimony and use of public domain measures to facilitate clinical translation.

METHODS

Cognitively unimpaired participants aged 65 to 85 at baseline with amyloid PET imaging were included, yielding 428 amyloid negative (A-) and 186 amyloid positive (A+) individuals with 7 years mean follow-up. Sensitivity to amyloid-related cognitive decline was examined using slope estimates derived from linear mixed models (difference in annualized change across A+ and A- groups). We compared differences in rates of change between Mayo-PACC and other composites (A+ > A- indicating more significant decline in A+).

RESULTS

All composites showed sensitivity to amyloid-related longitudinal cognitive decline (A+ > A- annualized change p < 0.05). Comparisons revealed that Mayo-PACC (AVLT sum of trials 1-5+6+delay, Trails B, animal fluency) showed comparable longitudinal sensitivity to other composites.

DISCUSSION

Mayo-PACC performs similarly to other composites and can be directly translated to the clinic.

Cognitive reserve moderates the association between cerebral blood flow and language performance in older adults with mild cognitive impairment

Higher cognitive reserve (CR) may offer protection from cognitive changes associated with reduced cerebral blood flow (CBF). We investigated CR as a moderator of the effect of CBF on cognition in older adults with mild cognitive impairment (MCI; N = 46) and those who are cognitively unimpaired (CU; N = 101). Participants underwent arterial spin labeling MRI, which was used to quantify CBF in 4 a priori regions. Estimated verbal intelligence quotient (VIQ) served as a proxy for CR. Multiple linear regressions examined whether VIQ moderated associations between CBF and cognition and whether this differed by cognitive status. Outcomes included memory and language performance. There were 3-way interactions (CBF*VIQ*cognitive status) on category fluency when examining hippocampal, superior frontal, and inferior frontal CBF. Follow-up analyses revealed that, within the MCI but not CU group, there were CBF*VIQ interactions on fluency in all a priori regions examined, where there were stronger, positive associations between CBF and fluency at higher VIQ. Conclusion: In MCI, higher CR plays a role in strengthening CBF-fluency associations.

Discovery of novel CSF biomarkers to predict progression in dementia using machine learning

Providing an accurate prognosis for individual dementia patients remains a challenge since they greatly differ in rates of cognitive decline. In this study, we used machine learning techniques with the aim to identify cerebrospinal fluid (CSF) biomarkers that predict the rate of cognitive decline within dementia patients. First, longitudinal mini-mental state examination scores (MMSE) of 210 dementia patients were used to create fast and slow progression groups. Second, we trained random forest classifiers on CSF proteomic profiles and obtained a well-performing prediction model for the progression group (ROC-AUC = 0.82). As a third step, Shapley values and Gini feature importance measures were used to interpret the model performance and identify top biomarker candidates for predicting the rate of cognitive decline. Finally, we explored the potential for each of the 20 top candidates in internal sensitivity analyses. TNFRSF4 and TGF [Formula: see text]-1 emerged as the top markers, being lower in fast-progressing patients compared to slow-progressing patients. Proteins of which a low concentration was associated with fast progression were enriched for cell signalling and immune response pathways. None of our top markers stood out as strong individual predictors of subsequent cognitive decline. This could be explained by small effect sizes per protein and biological heterogeneity among dementia patients. Taken together, this study presents a novel progression biomarker identification framework and protein leads for personalised prediction of cognitive decline in dementia.

Validation study of "Santé-Cerveau", a digital tool for early cognitive changes identification

BACKGROUND

There is a need for a reliable, easy-to-use, widely available, and validated tool for timely cognitive impairment identification. We created a computerized cognitive screening tool (Santé-Cerveau digital tool (SCD-T)) including validated questionnaires and the following neuropsychological tests: 5 Word Test (5-WT) for episodic memory, Trail Making Test (TMT) for executive functions, and a number coding test (NCT) adapted from the Digit Symbol Substitution Test for global intellectual efficiency. This study aimed to evaluate the performance of SCD-T to identify cognitive deficit and to determine its usability.

METHODS

Three groups were constituted including 65 elderly Controls, 64 patients with neurodegenerative diseases (NDG): 50 AD and 14 non-AD, and 20 post-COVID-19 patients. The minimum MMSE score for inclusion was 20. Association between computerized SCD-T cognitive tests and their standard equivalent was assessed using Pearson's correlation coefficients. Two algorithms (a simple clinician-guided algorithm involving the 5-WT and the NCT; and a machine learning classifier based on 8 scores from the SCD-T tests extracted from a multiple logistic regression model, and data from the SCD-T questionnaires) were evaluated. The acceptability of SCD-T was investigated through a questionnaire and scale.

RESULTS

AD and non-AD participants were older (mean ± standard deviation (SD): 72.61 ± 6.79 vs 69.91 ± 4.86 years old, p = 0.011) and had a lower MMSE score (Mean difference estimate ± standard error: 1.74 ± 0.14, p < 0.001) than Controls; post-COVID-19 patients were younger than Controls (mean ± SD: 45.07 ± 11.36 years old, p < 0.001). All the computerized SCD-T cognitive tests were significantly associated with their reference version. In the pooled Controls and NDG group, the correlation coefficient was 0.84 for verbal memory, -0.60 for executive functions, and 0.72 for global intellectual efficiency. The clinician-guided algorithm demonstrated 94.4% ± 3.8% sensitivity and 80.5% ± 8.7% specificity, and the machine learning classifier 96.8% ± 3.9% sensitivity and 90.7% ± 5.8% specificity. The acceptability of SCD-T was good to excellent.

CONCLUSIONS

We demonstrate the high accuracy of SCD-T in screening cognitive disorders and its good acceptance even in individuals with prodromal and mild dementia stages. SCD-T would be useful in primary care to faster refer subjects with significant cognitive impairment (and limit unnecessary referrals) to specialized consultation, improve the AD care pathway and the pre-screening in clinical trials.

Classification of Alzheimer's disease using robust TabNet neural networks on genetic data

Alzheimer's disease (AD) is one of the most common neurodegenerative diseases and its onset is significantly associated with genetic factors. Being the capabilities of high specificity and accuracy, genetic testing has been considered as an important technique for AD diagnosis. In this paper, we presented an improved deep learning (DL) algorithm, namely differential genes screening TabNet (DGS-TabNet) for AD binary and multi-class classifications. For performance evaluation, our proposed approach was compared with three novel DLs of multi-layer perceptron (MLP), neural oblivious decision ensembles (NODE), TabNet as well as five classical machine learnings (MLs) including decision tree (DT), random forests (RF), gradient boosting decision tree (GBDT), light gradient boosting machine (LGBM) and support vector machine (SVM) on the public data set of gene expression omnibus (GEO). Moreover, the biological interpretability of global important genetic features implemented for AD classification was revealed by the Kyoto encyclopedia of genes and genomes (KEGG) and gene ontology (GO). The results demonstrated that our proposed DGS-TabNet achieved the best performance with an accuracy of 93.80% for binary classification, and with an accuracy of 88.27% for multi-class classification. Meanwhile, the gene pathway analyses demonstrated that there existed two most important global genetic features of AVIL and NDUFS4 and those obtained 22 feature genes were partially correlated with AD pathogenesis. It was concluded that the proposed DGS-TabNet could be used to detect AD-susceptible genes and the biological interpretability of susceptible genes also revealed the potential possibility of being AD biomarkers.

Predicting conversion from mild cognitive impairment to Alzheimer's disease with multimodal latent factors

INTRODUCTION

We studied the ability of latent factor scores to predict conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) and investigated whether multimodal factor scores improve predictive power, relative to single-modal factor scores.

METHOD

We conducted exploratory factor analyses (EFAs) and confirmatory factor analyses (CFAs) of the baseline data of MCI subjects in the Alzheimer's Disease Neuroimaging Initiative (ADNI) to generate factor scores for three data modalities: neuropsychological (NP), magnetic resonance imaging (MRI), and cerebrospinal fluid (CSF). Factor scores from single or multiple modalities were entered in logistic regression models to predict MCI to AD conversion for 160 ADNI subjects over a 2-year interval.

RESULTS

NP factors attained an area under the curve (AUC) of .80, with a sensitivity of .66 and a specificity of .77. MRI factors reached a comparable level of performance (AUC = .80, sensitivity = .66, specificity = .78), whereas CSF factors produced weaker prediction (AUC = .70, sensitivity = .56, specificity = .79). Combining NP factors with MRI or CSF factors produced better prediction than either MRI or CSF factors alone. Similarly, adding MRI factors to NP or CSF factors produced improvements in prediction relative to NP or CSF factors alone. However, adding CSF factors to either NP or MRI factors produced no improvement in prediction.

CONCLUSIONS

Latent factor scores provided good accuracy for predicting MCI to AD conversion. Adding NP or MRI factors to factors from other modalities enhanced predictive power but adding CSF factors did not.

Categorical Perception of Lexical Tones in Mandarin-Speaking Seniors

PURPOSE

This study aims to investigate the different degeneration processes of categorical perception (CP) of Mandarin lexical tones in the normal aging population and the pathological aging population with mild cognitive impairment (MCI).

METHOD

In Experiment I, we compared the identification and discrimination of Tone 1 and Tone 2 across young adults, seniors aged 60-65 years, and older seniors aged 75-80 years with normal cognitive abilities. In Experiment II, we compared lexical tone identification and discrimination across young adults, healthy seniors, and age-matched seniors with MCI.

RESULTS

In Experiment I, tone perception was intact in seniors aged below 65 years. Those aged above 75 years could also maintain normal tone identification, whereas they showed poorer tone discrimination correlated with age-related poorer hearing level. In Experiment II, healthy seniors showed normal CP of Mandarin tones. Tone identification was also normal in those with MCI, whereas their tone discrimination had significantly degenerated.

CONCLUSIONS

In the normal aging population, age-related hearing loss decreased signal audibility, accounting for poorer discrimination of Mandarin lexical tones in seniors above 75 years. In the pathological aging population with MCI, the poorer discrimination of lexical tones may be attributed to the additive effect of age, hearing loss, and cognitive impairment (e.g., impaired working memory and long-term phonological memory). This study uncovered the roles of low-level sensory processing and high-level cognitive processing in lexical tone perception in the Chinese aging population.

A Novel Method for Establishing Functional Change in Older Adults With Cognitive Impairment

OBJECTIVE

The aim was to set syndrome stage-specific (eg, cognitively unimpaired, severe dementia) metrics for functional change.

METHODS

We selected 18,097 individuals who participated in 2 National Alzheimer's Coordinating Center visits between June 2005 and May 2020, with completed collateral rating of functioning on activities of daily living assessed by the Functional Activities Questionnaire.Both distribution-based (ie, regression-based reliable change indices) and anchor-based (ie, typical change associated with advancing a syndromal stage for clinically meaningful difference) methods were applied for individuals classified as: unimpaired cognition, mild cognitive impairment, mild dementia, moderate dementia, or severe dementia.

RESULTS

There were marked differences in the distribution of functional ratings depending on their syndromal stage. There were also differences in the functional change associated with advancing across different syndromal stages. These informed stage-specific metrics for reliable change indices and clinically meaningful differences.

CONCLUSIONS

Our indices provide a hitherto unavailable method that allows clinicians to determine whether observed functional change is reliable or meaningful based on syndromal stage.

Contribution of Memory Tests to Early Identification of Conversion from Amnestic Mild Cognitive Impairment to Dementia

Background:

Memory tests using controlled encoding and cued recall paradigm (CECR) have been shown to identify prodromal Alzheimer’s disease (AD), but information about the effectiveness of CECR compared to other memory tests in predicting clinical progression is missing.

Objective:

The aim was to examine the predictive ability of a memory test based on the CECR paradigm in comparison to other memory/non-memory tests for conversion to dementia in patients with amnestic mild cognitive impairment (aMCI).

Methods:

270 aMCI patients from the clinical-based Czech Brain Aging Study underwent a comprehensive neuropsychological assessment including the Enhanced Cued Recall test (ECR), a memory test with CECR, two verbal memory tests without controlled encoding: the Auditory Verbal Learning Test (AVLT) and Logical memory test (LM), a visuospatial memory test: the Rey-Osterrieth Complex Figure test, and cognitive testing based on the Uniform Data Set battery. The patients were followed prospectively. Conversion to dementia as a function of cognitive performance was examined using Cox proportional hazard models.

Results:

144 (53%) patients converted to dementia. Most converters (89%) developed dementia due to AD or mixed (AD and vascular) dementia. Comparing the four memory tests, the delayed recall scores on AVLT and LM best predicted conversion to dementia. Adjusted hazard ratios (HR) of immediate recall scores on ECR, AVLT, and LM were similar to the HR of categorical verbal fluency.

Conclusion:

Using the CECR memory paradigm in assessment of aMCI patients has no superiority over verbal and non-verbal memory tests without cued recall in predicting conversion to dementia.

Item-Level Story Recall Predictors of Amyloid-Beta in Late Middle-Aged Adults at Increased Risk for Alzheimer's Disease

Background

Story recall (SR) tests have shown variable sensitivity to rate of cognitive decline in individuals with Alzheimer's disease (AD) biomarkers. Although SR tasks are typically scored by obtaining a sum of items recalled, item-level analyses may provide additional sensitivity to change and AD processes. Here, we examined the difficulty and discrimination indices of each item from the Logical Memory (LM) SR task, and determined if these metrics differed by recall conditions, story version (A vs. B), lexical categories, serial position, and amyloid status.

Methods

n = 1,141 participants from the Wisconsin Registry for Alzheimer's Prevention longitudinal study who had item-level data were included in these analyses, as well as a subset of n = 338 who also had amyloid positron emission tomography (PET) imaging. LM data were categorized into four lexical categories (proper names, verbs, numbers, and "other"), and by serial position (primacy, middle, and recency). We calculated difficulty and discriminability/memorability by item, category, and serial position and ran separate repeated measures ANOVAs for each recall condition, lexical category, and serial position. For the subset with amyloid imaging, we used a two-sample t-test to examine whether amyloid positive (Aβ+) and amyloid negative (Aβ-) groups differed in difficulty or discrimination for the same summary metrics.

Results

In the larger sample, items were more difficult (less memorable) in the delayed recall condition across both story A and story B. Item discrimination was higher at delayed than immediate recall, and proper names had better discrimination than any of the other lexical categories or serial position groups. In the subsample with amyloid PET imaging, proper names were more difficult for Aβ+ than Aβ-; items in the verb and "other" lexical categories and all serial positions from delayed recall were more discriminate for the Aβ+ group compared to the Aβ- group.

Conclusion

This study provides empirical evidence that both LM stories are effective at discriminating ability levels and amyloid status, and that individual items vary in difficulty and discrimination by amyloid status, while total scores do not. These results can be informative for the future development of sensitive tasks or composite scores for early detection of cognitive decline.

The Role of Amyloid PET in Imaging Neurodegenerative Disorders: A Review

Imaging of amyloid deposition using PET has been available in research studies for 2 decades and has been approved for clinical use by the U.S. Food and Drug Administration, the European Medicines Agency, and other regulatory agencies around the world. Amyloid PET is a crucial tool for the diagnosis of Alzheimer disease, as it allows the noninvasive detection of amyloid plaques, a core neuropathologic feature that defines the disease. The clinical use of amyloid PET is expected to increase with recent accelerated approval in the United States of aducanumab, an antiamyloid monoclonal antibody, for the treatment of mild cognitive impairment and mild dementia due to Alzheimer disease. However, amyloid pathology can also be found in cognitively unimpaired older adults and in patients with other neurodegenerative disorders. The aim of this review is to provide an up-to-date overview of the application of amyloid PET in neurodegenerative diseases. We provide an in-depth analysis of the clinical, pathologic, and imaging correlates; a comparison with other available biomarkers; and a review of the application of amyloid PET in clinical trials and clinical utility studies.

Association of Genetic Variants Linked to Late-Onset Alzheimer Disease With Cognitive Test Performance by Midlife

IMPORTANCE

Identifying the youngest age when Alzheimer disease (AD) influences cognition and the earliest affected cognitive domains will improve understanding of the natural history of AD and approaches to early diagnosis.

OBJECTIVE

To evaluate the age at which cognitive differences between individuals with higher compared with lower genetic risk of AD are first apparent and which cognitive assessments show the earliest difference.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study used data from UK Biobank participants of European genetic ancestry, aged 40 years or older, who contributed genotypic and cognitive test data from January 1, 2006, to December 31, 2015. Data analysis was performed from March 10, 2020, to January 4, 2022.

EXPOSURE

The AD genetic risk score (GRS), which is a weighted sum of 23 single-nucleotide variations.

MAIN OUTCOMES AND MEASURES

Seven cognitive tests were administered via touchscreen at in-person visits or online. Cognitive domains assessed included fluid intelligence, episodic memory, processing speed, executive functioning, and prospective memory. Multiple cognitive measures were derived from some tests, yielding 32 separate measures. Interactions between age and AD-GRS for each of the 32 cognitive measures were tested with linear regression using a Bonferroni-corrected P value threshold. For cognitive measures with significant evidence of age by AD-GRS interaction, the youngest age of interaction was assessed with new regression models, with nonlinear specification of age terms. Models with youngest age of interaction from 40 to 70 years, in 1-year increments, were compared, and the best-fitting model for each cognitive measure was chosen. Results across cognitive measures were compared to determine which cognitive indicators showed earliest AD-related change.

RESULTS

A total of 405 050 participants (mean [SD] age, 57.1 [7.9] years; 54.1% female) were included. Sample sizes differed across cognitive tests (from 12 455 to 404 682 participants). The AD-GRS significantly modified the association with age on 13 measures derived from the pairs matching (range in difference in mean cognition per decade increase in age for 1-SD higher AD-GRS, 2.5%-11.5%), symbol digit substitution (range in difference in mean cognition per decade increase in age for 1-SD higher AD-GRS, 2.0%-5.8%), and numeric memory tests (difference in mean cognition per decade increase in age for 1-SD higher AD-GRS, 8.8%) (P = 1.56 × 10-3). Best-fitting models suggested that cognitive scores of individuals with a high vs low AD-GRS began to diverge by 56 years of age for all 13 measures and by 47 years of age for 9 measures.

CONCLUSIONS AND RELEVANCE

In this cross-sectional study, by early midlife, subtle differences in memory and attention were detectable among individuals with higher genetic risk of AD.

Monthly At-Home Computerized Cognitive Testing to Detect Diminished Practice Effects in Preclinical Alzheimer's Disease

Introduction: We investigated whether monthly assessments of a computerized cognitive composite (C3) could aid in the detection of differences in practice effects (PE) in clinically unimpaired (CU) older adults, and whether diminished PE were associated with Alzheimer's disease (AD) biomarkers and annual cognitive decline. Materials and Methods: N = 114 CU participants (age 77.6 ± 5.0, 61% female, MMSE 29 ± 1.2) from the Harvard Aging Brain Study completed the self-administered C3 monthly, at-home, on an iPad for one year. At baseline, participants underwent in-clinic Preclinical Alzheimer's Cognitive Composite-5 (PACC5) testing, and a subsample (n = 72, age = 77.8 ± 4.9, 59% female, MMSE 29 ± 1.3) had 1-year follow-up in-clinic PACC5 testing available. Participants had undergone PIB-PET imaging (0.99 ± 1.6 years before at-home baseline) and Flortaucipir PET imaging (n = 105, 0.62 ± 1.1 years before at-home baseline). Linear mixed models were used to investigate change over months on the C3 adjusting for age, sex, and years of education, and to extract individual covariate-adjusted slopes over the first 3 months. We investigated the association of 3-month C3 slopes with global amyloid burden and tau deposition in eight predefined regions of interest, and conducted Receiver Operating Characteristic analyses to examine how accurately 3-month C3 slopes could identify individuals that showed >0.10 SD annual decline on the PACC-5. Results: Overall, individuals improved on all C3 measures over 12 months (β = 0.23, 95% CI [0.21-0.25], p < 0.001), but improvement over the first 3 months was greatest (β = 0.68, 95% CI [0.59-0.77], p < 0.001), suggesting stronger PE over initial repeated exposures. However, lower PE over 3 months were associated with more global amyloid burden (r = -0.20, 95% CI [-0.38 - -0.01], p = 0.049) and tau deposition in the entorhinal cortex (r = -0.38, 95% CI [-0.54 - -0.19], p < 0.001) and inferior-temporal lobe (r = -0.23, 95% CI [-0.41 - -0.02], p = 0.03). 3-month C3 slopes exhibited good discriminative ability to identify PACC-5 decliners (AUC 0.91, 95% CI [0.84-0.98]), which was better than baseline C3 (p < 0.001) and baseline PACC-5 scores (p = 0.02). Conclusion: While PE are commonly observed among CU adults, diminished PE over monthly cognitive testing are associated with greater AD biomarker burden and cognitive decline. Our findings imply that unsupervised computerized testing using monthly retest paradigms can provide rapid detection of diminished PE indicative of future cognitive decline in preclinical AD.

Cognitive dysfunction and cerebral volumetric deficits in individuals with Alzheimer's disease, alcohol use disorder, and dual diagnosis

Epidemiological surveys suggest that excessive drinking is associated with higher risk of Alzheimer's disease (AD). The present study utilized data from the National Alzheimer's Coordinating Center to examine cognition as well as gray/white matter and ventricular volumes among participants with AD and alcohol use disorder (AD/AUD, n = 52), AD only (n = 701), AUD only (n = 67), and controls (n = 1283). AUD diagnosis was associated with higher Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) in AD than in non-AD. AD performed worse on semantic fluency and Trail Making Test A + B (TMT A + B) and showed smaller total GMV, WMV, and larger ventricular volume than non-AD. AD had smaller regional GMV in the inferior/superior parietal cortex, hippocampal formation, occipital cortex, inferior frontal gyrus, posterior cingulate cortex, and isthmus cingulate cortex than non-AD. AUD had significantly smaller somatomotor cortical GMV and showed a trend towards smaller volume in the hippocampal formation, relative to non-AUD participants. Misuse of alcohol has an additive effect on dementia severity among AD participants. Smaller hippocampal volume is a common feature of both AD and AUD. Although AD is associated with more volumetric deficits overall, AD and AUD are associated with atrophy in largely distinct brain regions.

Adherence to Mediterranean Diet and Cognitive Abilities in the Greek Cohort of Epirus Health Study

The Mediterranean diet is commonly proposed as a major modifiable protective factor that may delay cognitive impairment in the elderly. The aim of the study was to investigate the cross-sectional association of adherence to the Mediterranean diet with cognitive abilities in a younger Greek population. A total of 1201 healthy adults aged 21-77 years (mean: 47.8) from the Epirus Health Study cohort were included in the analysis. Adherence to the Mediterranean diet was measured using the 14-point Mediterranean Diet Adherence Screener (MEDAS) and cognition was measured using the Trail Making Test, the Verbal Fluency test and the Logical Memory test. Statistical analysis was performed using multiple linear regression models adjusted for age, sex, education, body mass index, smoking status, alcohol consumption and physical activity. Overall, no association was found between the MEDAS score and cognitive tests, which could be explained by the young mean age and high level of education of the participants. Future studies should target young and middle-aged individuals to gain further understanding of the association between Mediterranean diet and cognition in this age group.

The Analysis of Oxidative Stress Markers May Increase the Accuracy of the Differential Diagnosis of Alzheimer's Disease with and without Depression

Introduction

The aim of work is to assess the usefulness of oxidative stress parameters in the differential diagnosis of dementia of the Alzheimer’s type and dementia of the Alzheimer’s type with coexisting depression.

Methods

The study involved three groups of people: patients with Alzheimer’s disease (AD) (AD; N=27), patients with Alzheimer’s disease and depression (D) (AD+D; N=30), and a control group that consisted of people without dementia and without depression (C; N=24). The assessment of cognitive functioning was carried out using among alia, Auditory Verbal Learning Test and Verbal Fluency Test. Furthermore, we determined the activity of superoxide dismutase (SOD-1) and superoxide anion radical.

Results

Multiple models with different combinations of independent variables showed that SOD together with Rey delayed recall were the best significant predictors of AD with the area under curve (AUC) of 0.893 (p = 0.001) and superoxide anion radical (O2^•−) together with verbal fluency – sharp objects were the best significant predictors of AD +D diagnosis with the AUC of 0.689 (p = 0.034).

Conclusion

This study confirmed the value of neuropsychological diagnosis and analysis of oxidative stress markers in the diagnosis of AD and major depressive disorder (MDD) in the course of AD. The combination of the use of biochemical markers and neuropsychological tests seems particularly important for differential diagnosis.

Decline in cognitively complex everyday activities accelerates along the Alzheimer's disease continuum

BACKGROUND

Impairment in daily functioning is a clinical hallmark of dementia. Difficulties with "instrumental activities of daily living" (IADL) seem to increase gradually over the course of Alzheimer's disease (AD), before dementia onset. However, it is currently not well established how difficulties develop along the preclinical and prodromal stages of AD. We aimed to investigate the trajectories of decline in IADL performance, as reported by a study partner, along the early stages of AD.

METHODS

In a longitudinal multicenter study, combining data from community-based and memory clinic cohorts, we included 1555 individuals (mean age 72.5 ± 7.8 years; 50% female) based on availability of amyloid biomarkers, longitudinal IADL data, and clinical information at baseline. Median follow-up duration was 2.1 years. All amyloid-positive participants (n = 982) were classified into the National Institute on Aging-Alzheimer's Association (NIA-AA) clinical stages ranging from preclinical AD (1) to overt dementia (4+). Cognitively normal amyloid-negative individuals (n = 573) served as a comparison group. The total scores of three study-partner reported IADL questionnaires were standardized.

RESULTS

The rate of decline in cognitively normal (stage 1) individuals with and without abnormal amyloid did not differ (p = .453). However, from stage 2 onwards, decline was significantly faster in individuals on the AD continuum (B [95%CI] = - 0.32 [- 0.55, - 0.09], p = .007). The rate of decline increased with each successive stage: one standard deviation (SD) unit per year in stage 3 (- 1.06 [- 1.27, - 0.85], p < .001) and nearly two SD units per year in stage 4+ (1.93 [- 2.19, - 1.67], p < .001). Overall, results were similar between community-based and memory clinic study cohorts.

CONCLUSIONS

Our results suggest that the rate of functional decline accelerates along the AD continuum, as shown by steeper rates of decline in each successive NIA-AA clinical stage. These results imply that incremental changes in function are a meaningful measure for early disease monitoring. Combined with the low-cost assessment, this advocates the use of these functional questionnaires for capturing the effects of early AD-related cognitive decline on daily life.